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Tick size and price diffusion

Author

Listed:
  • Gabriele La Spada
  • J. Doyne Farmer
  • Fabrizio Lillo

Abstract

A tick size is the smallest increment of a security price. It is clear that at the shortest time scale on which individual orders are placed the tick size has a major role which affects where limit orders can be placed, the bid-ask spread, etc. This is the realm of market microstructure and there is a vast literature on the role of tick size on market microstructure. However, tick size can also affect price properties at longer time scales, and relatively less is known about the effect of tick size on the statistical properties of prices. The present paper is divided in two parts. In the first we review the effect of tick size change on the market microstructure and the diffusion properties of prices. The second part presents original results obtained by investigating the tick size changes occurring at the New York Stock Exchange (NYSE). We show that tick size change has three effects on price diffusion. First, as already shown in the literature, tick size affects price return distribution at an aggregate time scale. Second, reducing the tick size typically leads to an increase of volatility clustering. We give a possible mechanistic explanation for this effect, but clearly more investigation is needed to understand the origin of this relation. Third, we explicitly show that the ability of the subordination hypothesis in explaining fat tails of returns and volatility clustering is strongly dependent on tick size. While for large tick sizes the subordination hypothesis has significant explanatory power, for small tick sizes we show that subordination is not the main driver of these two important stylized facts of financial market.

Suggested Citation

  • Gabriele La Spada & J. Doyne Farmer & Fabrizio Lillo, 2010. "Tick size and price diffusion," Papers 1009.2329, arXiv.org, revised Oct 2010.
  • Handle: RePEc:arx:papers:1009.2329
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    File URL: http://arxiv.org/pdf/1009.2329
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    References listed on IDEAS

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    1. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    2. Bence Toth & Janos Kertesz, 2009. "The Epps effect revisited," Quantitative Finance, Taylor & Francis Journals, vol. 9(7), pages 793-802.
    3. Ahn, Hee-Joon & Cao, Charles Q. & Choe, Hyuk, 1998. "Decimalization and competition among stock markets: Evidence from the Toronto Stock Exchange cross-listed securities," Journal of Financial Markets, Elsevier, vol. 1(1), pages 51-87, April.
    4. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    5. Huang, Roger D. & Stoll, Hans R., 2001. "Tick Size, Bid-Ask Spreads, and Market Structure," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 36(4), pages 503-522, December.
    6. Goldstein, Michael A. & A. Kavajecz, Kenneth, 2000. "Eighths, sixteenths, and market depth: changes in tick size and liquidity provision on the NYSE," Journal of Financial Economics, Elsevier, vol. 56(1), pages 125-149, April.
    7. J. Doyne Farmer & Laszlo Gillemot & Fabrizio Lillo & Szabolcs Mike & Anindya Sen, 2004. "What really causes large price changes?," Quantitative Finance, Taylor & Francis Journals, vol. 4(4), pages 383-397.
    8. Onnela, Jukka-Pekka & Töyli, Juuso & Kaski, Kimmo, 2009. "Tick size and stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(4), pages 441-454.
    9. Benoit Mandelbrot & Howard M. Taylor, 1967. "On the Distribution of Stock Price Differences," Operations Research, INFORMS, vol. 15(6), pages 1057-1062, December.
    10. Michael C. Munnix & Rudi Schafer & Thomas Guhr, 2010. "Impact of the tick-size on financial returns and correlations," Papers 1001.5124, arXiv.org, revised Jul 2010.
    11. Thierry Ané & Hélyette Geman, 2000. "Order Flow, Transaction Clock, and Normality of Asset Returns," Journal of Finance, American Finance Association, vol. 55(5), pages 2259-2284, October.
    12. Münnix, Michael C. & Schäfer, Rudi & Guhr, Thomas, 2010. "Impact of the tick-size on financial returns and correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4828-4843.
    13. Ahn, Hee-Joon & Cao, Charles Q. & Choe, Hyuk, 1996. "Tick Size, Spread, and Volume," Journal of Financial Intermediation, Elsevier, vol. 5(1), pages 2-22, January.
    14. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    Cited by:

    1. Thanos Verousis & Pietro Perotti & Georgios Sermpinis, 2018. "One size fits all? High frequency trading, tick size changes and the implications for exchanges: market quality and market structure considerations," Review of Quantitative Finance and Accounting, Springer, vol. 50(2), pages 353-392, February.
    2. La Spada Gabriele & Lillo Fabrizio, 2014. "The effect of round-off error on long memory processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(4), pages 445-482, September.

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